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http://hdl.handle.net/20.500.12386/29155
Titolo: | SAPREMO: a simplified algorithm for predicting detections of electromagnetic transients in surveys | Autori: | Vinciguerra, S. Branchesi, M. CIOLFI, RICCARDO Mandel, I. Neijssel, C. J. STRATTA, MARIA GIULIANA |
Data pubblicazione: | 2019 | Rivista: | MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY | Numero: | 484 | Fascicolo: | 1 | Da pagina:: | 332 | Abstract: | The multiwavelength detection of GW170817 has inaugurated multimessenger astronomy. The next step consists in interpreting observations coming from population of gravitational wave sources. We introduce SAPREMO, a tool aimed at predicting the number of electromagnetic signals characterized by a specific light curve and spectrum, expected in a particular sky survey. By looking at past surveys, SAPREMO allows us to constrain models of electromagnetic emission or event rates. Applying SAPREMO to proposed astronomical missions/observing campaigns provides a perspective on their scientific impact and tests the effect of adopting different observational strategies. For our first case study, we adopt a model of spin-down-powered X-ray emission predicted for a binary neutron star merger producing a long-lived neutron star. We apply SAPREMO on data collected by XMM-Newton and Chandra and during 10<SUP>4 </SUP>s of observations with the mission concept THESEUS. We demonstrate that our emission model and binary neutron star merger rate imply the presence of some signals in the XMM-Newton catalogues. We also show that the new class of X-ray transients found by Bauer et al. in the Chandra Deep Field-South is marginally consistent with the expected rate. Finally, by studying the mission concept THESEUS, we demonstrate the substantial impact of a much larger field of view in searches of X-ray transients. | URI: | http://hdl.handle.net/20.500.12386/29155 | URL: | https://academic.oup.com/mnras/article-abstract/484/1/332/5256663?redirectedFrom=fulltext | ISSN: | 0035-8711 | DOI: | 10.1093/mnras/sty3490 | Bibcode ADS: | 2019MNRAS.484..332V | Fulltext: | open |
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